Inhibition of the precursor and mature forms of HIV-1 protease as a tool for drug evaluation

Investigating the combination of Temsavir and entry inhibitors on HIV replication: Synergistic and antagonistic effects observed against various R5-tropic envelopes

HIV is still a pandemic; antiretroviral therapeutics for preventing and treating HIV infection continue to present significant challenges. The demand for new drugs and effective treatments remains ongoing. Here, we investigated the effects of combining Temsavir with other HIV entry inhibitors, including CD4 mimetic BNM-III-170, T20 or enfuvirtide, Ibalizumab, and Maraviroc. Our results show that TMR demonstrates both synergistic and antagonistic activity when combined those other entry inhibitors, depending on the concentration and the specific envelope used. Results suggest that while low-dose combinations, especially using Temsavir and CD4 mimetic, exhibited antagonistic effects, Temsavir showed synergy at low and medium concentrations in combination with enfuvirtide, Ibalizumab, and Maraviroc. These results are promising for the potential of co-administrating antiretrovirals for HIV treatment and highlights the importance of developing advanced antiviral strategies. On the other hand, the variable responses against different R5-tropic envelopes underscore the complexity of designing universally effective combination antiviral therapies.

HIV OctaScanner: A Machine Learning Approach to Unveil Proteolytic Cleavage Dynamics in HIV-1 Protease Substrates

The rise of resistance to antiretroviral drugs due to mutations in human immunodeficiency virus-1 (HIV-1) protease is a major obstacle to effective treatment. These mutations alter the drug-binding pocket of the protease and reduce the drug efficacy by disrupting interactions with inhibitors. Traditional methods, such as biochemical assays and structural biology, are crucial for studying enzyme function but are time-consuming and labor-intensive. To address these challenges, we developed HIV OctaScanner, a machine learning algorithm that predicts the proteolytic cleavage activity of octameric substrates at the HIV-1 protease cleavage sites. The algorithm uses a Random Forest (RF) classifier and achieves a prediction accuracy of 89% in the identification of cleavable octamers. This innovative approach facilitates the rapid screening of potential substrates for HIV-1 protease, providing critical insights into enzyme function and guiding the development of more effective therapeutic strategies. By improving the accuracy of substrate identification, HIV OctaScanner has the potential to support the development of next generation antiretroviral treatments.

The zymogenic form of SARS-CoV-2 main protease: A discrete target for drug discovery

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro) autocatalytically releases itself out of the viral polyprotein to form a fully active mature dimer in a manner that is not fully understood. Here, we introduce several tools to help elucidate differences between cis (intramolecular) and trans (intermolecular) proteolytic processing and to evaluate inhibition of precursor Mpro. We found that many mutations at the P1 position of the N-terminal autoprocessing site do not block cis autoprocessing but do inhibit trans processing. Notably, substituting the WT glutamine at the P1 position with isoleucine retains Mpro in an unprocessed precursor form that can be purified and further studied. We also developed a cell-based reporter assay suitable for compound library screening and evaluation in HEK293T cells. This assay can detect both overall Mpro inhibition and the fraction of uncleaved precursor form of Mpro through separable fluorescent signals. We observed that inhibitory compounds preferentially block mature Mpro. Bofutrelvir and a novel compound designed in-house showed the lowest selectivity between precursor and mature Mpro, indicating that inhibition of both forms may be possible. Additionally, we observed positive modulation of precursor activity at low concentrations of inhibitors. Our findings help expand understanding of the SARS-CoV-2 viral life cycle and may facilitate development of strategies to target precursor form of Mpro for inhibition or premature activation of Mpro.

Mechanism and Kinetics of HIV-1 Protease Activation

The HIV-1 protease is a critical enzyme for viral replication. Because protease activity is necessary to generate mature infectious virions, it is a primary target of antiretroviral treatment. Here, we provide an overview of the mechanisms regulating protease activation and the methods available to assess protease activity. Finally, we will highlight some of the key discoveries regarding the kinetics of protease activation from the last decade, including how the manipulation of activation kinetics may provide novel HIV-1 treatment strategies.

Viral proteases as therapeutic targets

Some medically important viruses-including retroviruses, flaviviruses, coronaviruses, and herpesviruses-code for a protease, which is indispensable for viral maturation and pathogenesis. Viral protease inhibitors have become an important class of antiviral drugs. Development of the first-in-class viral protease inhibitor saquinavir, which targets HIV protease, started a new era in the treatment of chronic viral diseases. Combining several drugs that target different steps of the viral life cycle enables use of lower doses of individual drugs (and thereby reduction of potential side effects, which frequently occur during long term therapy) and reduces drug-resistance development. Currently, several HIV and HCV protease inhibitors are routinely used in clinical practice. In addition, a drug including an inhibitor of SARS-CoV-2 main protease, nirmatrelvir (co-administered with a pharmacokinetic booster ritonavir as Paxlovid®), was recently authorized for emergency use. This review summarizes the basic features of the proteases of human immunodeficiency virus (HIV), hepatitis C virus (HCV), and SARS-CoV-2 and discusses the properties of their inhibitors in clinical use, as well as development of compounds in the pipeline.

Precursors of Viral Proteases as Distinct Drug Targets

Viral proteases are indispensable for successful virion maturation, thus making them a prominent drug target. Their enzyme activity is tightly spatiotemporally regulated by expression in the precursor form with little or no activity, followed by activation via autoprocessing. These cleavage events are frequently triggered upon transportation to a specific compartment inside the host cell. Typically, precursor oligomerization or the presence of a co-factor is needed for activation. A detailed understanding of these mechanisms will allow ligands with non-canonical mechanisms of action to be designed, which would specifically modulate the initial irreversible steps of viral protease autoactivation. Binding sites exclusive to the precursor, including binding sites beyond the protease domain, can be exploited. Both inhibition and up-regulation of the proteolytic activity of viral proteases can be detrimental for the virus. All these possibilities are discussed using examples of medically relevant viruses including herpesviruses, adenoviruses, retroviruses, picornaviruses, caliciviruses, togaviruses, flaviviruses, and coronaviruses.

Predicted antiviral drugs Darunavir, Amprenavir, Rimantadine and Saquinavir can potentially bind to neutralize SARS-CoV-2 conserved proteins

BACKGROUND

Novel Coronavirus disease 2019 or COVID-19 has become a threat to human society due to fast spreading and increasing mortality. It uses vertebrate hosts and presently deploys humans. Life cycle and pathogenicity of SARS-CoV-2 have already been deciphered and possible drug target trials are on the way.

RESULTS

The present study was aimed to analyze Non-Structural Proteins that include conserved enzymes of SARS-CoV-2 like papain-like protease, main protease, Replicase, RNA-dependent RNA polymerase, methyltransferase, helicase, exoribonuclease and endoribonucleaseas targets to all known drugs. A bioinformatic based web server Drug ReposeER predicted several drug binding motifs in these analyzed proteins. Results revealed that anti-viral drugs Darunavir,Amprenavir, Rimantadine and Saquinavir were the most potent to have 3D-drug binding motifs that were closely associated with the active sites of the SARS-CoV-2 enzymes .

CONCLUSIONS

 Repurposing of the antiviral drugs Darunavir, Amprenavir, Rimantadine and Saquinavir to treat COVID-19 patients could be useful that can potentially prevent human mortality.

Triterpenoid-PEG Ribbons Targeting Selectivity in Pharmacological Effects

(1) Background: To compare the effect of selected triterpenoids with their structurally resembling derivatives, designing of the molecular ribbons was targeted to develop compounds with selectivity in their pharmacological effects. (2) Methods: In the synthetic procedures, Huisgen 1,3-dipolar cycloaddition was applied as a key synthetic step for introducing a 1,2,3-triazole ring as a part of a junction unit in the molecular ribbons. (3) Results: The antimicrobial activity, antiviral activity, and cytotoxicity of the prepared compounds were studied. Most of the molecular ribbons showed antimicrobial activity, especially on Staphylococcus aureus, Pseudomonas aeruginosa, and Enterococcus faecalis, with a 50–90% inhibition effect (c = 25 µg·mL⁻¹). No target compound was effective against HSV-1, but 8a displayed activity against HIV-1 (EC₅₀ = 50.6 ± 7.8 µM). Cytotoxicity was tested on several cancer cell lines, and 6d showed cytotoxicity in the malignant melanoma cancer cell line (G-361; IC₅₀ = 20.0 ± 0.6 µM). Physicochemical characteristics of the prepared compounds were investigated, namely a formation of supramolecular gels and a self-assembly potential in general, with positive results achieved with several target compounds. (4) Conclusions: Several compounds of a series of triterpenoid molecular ribbons showed better pharmacological profiles than the parent compounds and displayed certain selectivity in their effects.

Darunavir-Resistant HIV-1 Protease Constructs Uphold a Conformational Selection Hypothesis for Drug Resistance

Multidrug resistance continues to be a barrier to the effectiveness of highly active antiretroviral therapy in the treatment of human immunodeficiency virus 1 (HIV-1) infection. Darunavir (DRV) is a highly potent protease inhibitor (PI) that is oftentimes effective when drug resistance has emerged against first-generation inhibitors. Resistance to darunavir does evolve and requires 10–20 amino acid substitutions. The conformational landscapes of six highly characterized HIV-1 protease (PR) constructs that harbor up to 19 DRV-associated mutations were characterized by distance measurements with pulsed electron double resonance (PELDOR) paramagnetic resonance spectroscopy, namely double electron–electron resonance (DEER). The results show that the accumulated substitutions alter the conformational landscape compared to PI-naïve protease where the semi-open conformation is destabilized as the dominant population with open-like states becoming prevalent in many cases. A linear correlation is found between values of the DRV inhibition parameter K_i and the open-like to closed-state population ratio determined from DEER. The nearly 50% decrease in occupancy of the semi-open conformation is associated with reduced enzymatic activity, characterized previously in the literature.

Enrichment of rare events using a multi-parameter high throughput microfluidic droplet sorter

High information content analysis, enrichment, and selection of rare events from a large population are of great importance in biological and biomedical research. The fluorescence lifetime of a fluorophore, a photophysical property which is independent of and complementary to fluorescence intensity, has been incorporated into various imaging and sensing techniques through microscopy, flow cytometry and droplet microfluidics. However, the throughput of fluorescence lifetime activated droplet sorting is orders of magnitude lower than that of fluorescence activated cell sorting, making it unattractive for applications such as directed evolution of enzymes, despite its highly effective compartmentalization of library members. We developed a microfluidic sorter capable of selecting fluorophores based on fluorescence lifetime and brightness at two excitation and emission colors at a maximum droplet rate of 2.5 kHz. We also present a novel selection strategy for efficiently analyzing and/or enriching rare fluorescent members from a large population which capitalizes on the Poisson distribution of analyte encapsulation into droplets. The effectiveness of the droplet sorter and the new selection strategy are demonstrated by enriching rare populations from a ∼108-member site-directed mutagenesis library of fluorescent proteins expressed in bacteria. This selection strategy can in principle be employed on many droplet sorting platforms, and thus can potentially impact broad areas of science where analysis and enrichment of rare events is needed.

Exploiting the unique features of Zika and Dengue proteases for inhibitor design

Zika and Dengue viruses have attracted substantial attention from researchers in light of recent outbreaks of Dengue fever and increases in cases of congenital microcephaly in areas with Zika incidence. This review summarizes the current state of knowledge about Zika and Dengue proteases. These enzymes have several interesting features: 1) NS3 serine protease requires the activating co-factor NS2B, which is anchored in the membrane of the endoplasmic reticulum; 2) NS2B displays extensive conformational dynamics; 3) NS3 is a multidomain protein with proteolytic, NTPase, RNA 5' triphosphatase and helicase activity and has many protein-protein interaction partners; 4) NS3 is autoproteolytically released from its precursor. Attempts to design tight-binding and specific active-site inhibitors are complicated by the facts that the substrate pocket of the NS2B-NS3 protease is flat and the active-site ligands are charged. The ionic character of potential active-site inhibitors negatively influences their cell permeability. Possibilities to block cis-autoprocessing of the protease precursor have recently been considered. Additionally, potential allosteric sites on NS2B-NS3 proteases have been identified and allosteric compounds have been designed to impair substrate binding and/or block the NS2B-NS3 interaction. Such compounds could be specific to viral proteases, without off-target effects on host serine proteases, and could have favorable pharmacokinetic profiles. This review discusses various groups of inhibitors of these proteases according to their mechanisms of action and chemical structures.

Targeting HIV-1 Protease Autoprocessing for High-throughput Drug Discovery and Drug Resistance Assessment

HIV-1 protease autoprocessing liberates the free mature protease from its Gag-Pol polyprotein precursor through a series of highly regulated autoproteolysis reactions. Herein, we report the development and validation (Z' ≥ 0.50) of a cell-based functional assay for high-throughput screening (HTS) of autoprocessing inhibitors using fusion precursors in combination with AlphaLISA (amplified luminescent proximity homogeneous assay ELISA). Through pilot screening of a collection of 130 known protease inhibitors, the AlphaLISA assay confirmed all 11 HIV protease inhibitors in the library capable of suppressing precursor autoprocessing at low micromolar concentrations. Meanwhile, other protease inhibitors had no impact on precursor autoprocessing. We next conducted HTS of ~23,000 compounds but found no positive hits. Such high selectivity is advantageous for large-scale HTS campaigns and as anticipated based on assay design because a positive hit needs simultaneously to be nontoxic, cell permeable, and inhibiting precursor autoprocessing. Furthermore, AlphaLISA quantification of fusion precursors carrying mutations known to cause resistance to HIV protease inhibitors faithfully recapitulated the reported resistance, suggesting that precursor autoprocessing is a critical step contributing to drug resistance. Taken together, this reported AlphaLISA platform will provide a useful tool for drug discovery targeting HIV-1 protease autoprocessing and for quantification of PI resistance.